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1. Radio dynamic zone management system for urban environments

   Bastidas, C; Doshi, J; Choudhury, M; Prabhakara, A; Adhikari, A; Hermstein, K; Singh, A; Li, Y; Chen, T; Jamieson, K; et al (May 2026, in Proc. National Radio Dynamic Zones (NRDZ) Workshop, 2026)

   The growing demand for wireless communications and the emergence of 5G and beyond-5G networks have made dynamic spectrum sharing and efficient radio frequency (RF) spectrum management critical challenges for both researchers and regulators. This paper presents the COSMOS Zone Management System (ZMS), a cloud-native, web-based spectrum coordination platform designed to enable dynamic electromagnetic spectrum sharing in dense urban environments. Developed as part of a multi-university NSF SII-NRDZ collaboration, the ZMS operates within the COSMOS PAWR testbed in West Harlem, New York City, inside an FCC-designated Innovation Zone. The system leverages Spectrum Consumption Models (SCMs) standardized under IEEE 1900.5.2 to formally characterize RF device spectrum use and execute Compatibility Test (CT) computations for interference analysis and spectrum use authorization. Built on a Kubernetes-based microservices architecture, the ZMS integrates real-time spectrum monitoring, automated compatibility testing, interference alarm management, and external tool integrations — including NG-Scope for LTE network telemetry and Geo2SigMap for 3D radio propagation modeling. Two representative use cases demonstrate the system’s planning and coordination capabilities. The results illustrate the ZMS’s ability to serve as both an operational spectrum management tool and a research platform for studying spectrum coexistence in complex urban RF environments. 

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2. Enhanced Real-Time Threat Detection in 5G Networks: A Self-Attention RNN Autoencoder Approach for Spectral Intrusion Analysis

   Kouchaki, Mohammadreza; Zhang, Minglong; Abdalla, Aly S; Lan, Guangchen; Brinton, Christopher G; Marojevic, Vuk (December 2024, 2024 22nd International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt))

   In the rapidly evolving landscape of 5G technology, safeguarding Radio Frequency (RF) environments against sophisticated intrusions is paramount, especially in dynamic spectrum access and management. This paper presents an enhanced experimental model that integrates a self-attention mechanism with a Recurrent Neural Network (RNN)-based autoencoder for the detection of anomalous spectral activities in 5G networks at the waveform level. Our approach, grounded in time-series analysis, processes in-phase and quadrature (I/Q) samples to identify irregularities that could indicate potential jamming attacks. The model's architecture, augmented with a self-attention layer, extends the capabilities of RNN autoen-coders, enabling a more nuanced understanding of temporal dependencies and contextual relationships within the RF spectrum. Utilizing a simulated 5G Radio Access Network (RAN) test-bed constructed with srsRAN 5G and Software Defined Radios (SDRs), we generated a comprehensive stream of data that reflects real-world RF spectrum conditions and attack scenarios. The model is trained to reconstruct standard signal behavior, establishing a normative baseline against which deviations, indicative of security threats, are identified. The proposed architecture is designed to balance between detection precision and computational efficiency, so the LSTM network, enriched with self-attention, continues to optimize for minimal execution latency and power consumption. Conducted on a real-world SDR-based testbed, our results demonstrate the model's improved performance and accuracy in threat detection. 

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3. LTE Spectrum Sharing Research Testbed: Integrated Hardware, Software, Network and Data

   https://doi.org/https://doi.org/10.1145/3131473.3131484  

   Marojevic, Vuk; Nealy, Randall; Reed, Jeffrey H. (October 2017, ACM WiNTECH 2017)

   This paper presents Virginia Tech’s wireless testbed supporting research on long-term evolution (LTE) signaling and radio frequency (RF) spectrum coexistence. LTE is continuously refined and new features released. As the communications contexts for LTE expand, new research problems arise and include operation in harsh RF signaling environments and coexistence with other radios. Our testbed provides an integrated research tool for investigating these and other research problems; it allows analyzing the severity of the problem, designing and rapidly prototyping solutions, and assessing them with standard-compliant equipment and test procedures. The modular testbed integrates general-purpose software-defined radio hardware, LTE-specific test equipment, RF components, free open-source and commercial LTE software, a configurable RF network and recorded radar waveform samples. It supports RF channel emulated and over-the-air radiated modes. The testbed can be remotely accessed and configured. An RF switching network allows for designing many different experiments that can involve a variety of real and virtual radios with support for multiple-input multiple-output (MIMO) antenna operation. We present the testbed, the research it has enabled and some valuable lessons that we learned and that may help designing, developing, and operating future wireless testbeds. 

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4. RF-Flashlight Testbed for Verification of Real-Time Geofencing of EESS Radiometers and Millimeter-Wave Ground-to-Satellite Propagation Models

   Eichen, E; Aradhya, A; Simić, L (June 2024, 2024 IEEE International Conference on Communications Workshops)

   A simple “RF-flashlight” (or ground-to-satellite) interference testbed is proposed to experimentally verify (i) real-time geofencing (RTG) for protecting passive Earth Exploration Satellite Services (EESS) radiometer measurements from 5G/6G mm-wave transmissions, and (ii) ground-to-satellite propagationmodels used in the interference modeling of this spectrumcoexistence scenario. RTG is a stronger EESS protectionmechanism than the current methodology recommended by theITU based on a worst-case interference threshold whilesimultaneously enabling dynamic spectrum sharing and coexistencewith 5G/6G wireless networks. Similarly, verifying moresophisticated RF propagation models that include ground topology,buildings, and non-line-of-sight paths will provide better estimatesof interference than the current ITU line-of-sight model and, thus,a more reliable basis for establishing a consensus among thespectrum stakeholders. 

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5. Dataset for Spectrum Coexistence in Passive Sensing and Wireless Communication

   https://doi.org/10.21227/968t-td34  

   Alam, Ahmed_Manavi Alam; Farhad, Md_Mehedi Farhad; Al-Qwider, Walaa Al-Qwider; Owfi, Ali Owfi; Koosha, Mohammad Koosha; Mastronarde, Nicholas Mastronarde; Afghah, Fatemeh Afghah; Marojevic, Vuk Marojevic; Kurum, Mehmet_ Kurum; Gurbuz, Ali Gurbuz (January 2024, IEEE DataPort)

   In our ever-expanding world of advanced satellite and communications systems, there's a growing challenge for passive radiometer sensors used in the Earth observation like 5G. These passive sensors are challenged by risks from radio frequency interference (RFI) caused by anthropogenic signals. To address this, we urgently need effective methods to quantify the impacts of 5G on Earth observing radiometers. Unfortunately, the lack of substantial datasets in the radio frequency (RF) domain, especially for active/passive coexistence, hinders progress. Our study introduces a controlled testbed featuring a calibrated L-band radiometer and a 5G wireless communication system. In a controlled chamber, this unique setup allows us to observe and quantify transmission effects across different frequency bands. By creating a comprehensive dataset, we aim to standardize and benchmark both wireless communication and passive sensing. With the ability to analyze raw measurements, our testbed facilitates RFI detection and mitigation, fostering the coexistence of wireless communication and passive sensing technologies while establishing crucial standards. 

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